A welding positioning tool applied to sheet metal parts of engineering machinery

Abstract

The application discloses a welding positioning tool applied to sheet metal parts of engineering machinery, and belongs to the technical field of welding, which comprises a measurement comparison module, a prediction and distribution clamping force module, a clamping execution mechanism, a load sensor and a cooperative compensation controller. The tool extracts the spatial posture deviation and the non-rigid deformation force characteristics of the workpiece, combines the thermal expansion and material phase change characteristics, calculates and dynamically distributes the clamping force for constraining the thermal instability of the workpiece. During the welding process, the load sensor is used to monitor the load fluctuation of each clamping point in real time, the cooperative compensation controller synchronously adjusts the output force of the clamping mechanism according to the load fluctuation, and the spatial motion posture of the welding end is corrected, so that the thermal deformation displacement of the workpiece is effectively offset.

Description

Technical Field

[0001] This invention belongs to the field of welding technology, and in particular relates to a welding positioning fixture for sheet metal parts of engineering machinery. Background Technology

[0002] During the welding process of traditional engineering machinery sheet metal parts, spatial orientation deviations and non-rigid deformation forces reflecting the residual stress state inside the parts often exist due to manufacturing errors. At the same time, during the welding and cooling process, the material is affected by phase transformation characteristics such as thermal expansion and volume expansion, which can easily lead to thermal instability.

[0003] Existing conventional welding fixtures typically employ static fixed clamping, which cannot dynamically distribute the clamping force in a non-uniform manner based on the local curvature changes at each clamping point and the interaction distance with the weld.

[0004] In addition, existing equipment lacks the ability to monitor the load fluctuations at the clamping point in real time, and it is also unable to coordinate the correction of the spatial motion posture of the welding robot according to the load changes, which ultimately makes it difficult to effectively offset the thermal deformation displacement of the workpiece, affecting the welding quality and dimensional accuracy. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a welding positioning fixture for sheet metal parts of engineering machinery, thus solving the aforementioned problems.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a welding positioning fixture for sheet metal parts of engineering machinery, comprising: The measurement and comparison module acquires the measured spatial data of the sheet metal parts and compares it with the theoretical design model to extract the spatial posture deviation of the workpiece and the non-rigid deformation force characteristics that reflect the residual stress state inside the parts. The total target clamping force prediction module calculates the total target clamping force to constrain the workpiece's thermal instability based on the spatial attitude deviation and non-rigid deformation force characteristics, combined with the phase transformation characteristics of the material. The clamping force distribution module dynamically distributes the total target clamping force to each actuator and determines the initial force component at each clamping point. Multiple clamping actuators are arranged around the workpiece to receive the initial component force output by the clamping force distribution module and apply it to the workpiece; A load sensor is installed on each of the clamping actuators to monitor load fluctuations at each clamping point in real time and output a load feedback signal. The collaborative compensation controller is communicatively connected to the load sensor, the clamping actuator, and the welding robot controller, respectively. It is used to synchronously adjust the output force of the clamping actuator according to the load feedback signal and collaboratively correct the spatial motion posture of the welding execution end to counteract the thermal deformation displacement of the workpiece.

[0007] Based on the above technical solutions, the present invention also provides the following optional technical solutions: A further technical solution: The measurement and comparison module utilizes the deviation field between spatial point cloud data and the theoretical numerical model, and decouples the global rigid body displacement deviation and local non-rigid deformation force through a singular value decomposition algorithm; its calculation process satisfies the following relationship: Solving for rigid body transformation parameters: The global rotation matrix and translation vector are solved by minimizing the Euclidean distance between point sets. , in, This is a global rotation matrix. It is a translation vector. The measured feature point spatial vector, For the spatial vector of the theoretical feature points; Calculation of non-rigid deformation force characteristics: After eliminating rigid body displacements using the solved global rotation matrix and translation vector, the equivalent deformation force is calculated. , in, For deformation and other effects, The material shear modulus This is a global rotation matrix. It is a translation vector. The measured feature point spatial vector, The spatial vector of the theoretical feature point.

[0008] Further technical solution: In the total target clamping force prediction module, the phase transformation characteristics include the microstructure volume expansion effect of the material during the welding cooling process. This module has a built-in phase transformation stress correction factor calculation unit, which is used to compensate for the load demand caused by thermal expansion and initial deformation energy. The compensation control calculation process is as follows: Define the thermal expansion stress components as: , in, This is the thermal expansion stress component. The elastic modulus of the material. This is the coefficient of linear expansion of the material. This is the peak welding temperature. The initial ambient temperature; The phase transformation stress correction factor output by the phase transformation stress correction factor calculation unit is set as follows: , in, This is the phase transformation stress correction factor. This represents the rate of change per unit volume during the phase transition process. The stress transfer coefficient of the tissue. Peak temperature The phase transition initiation temperature, is the Heaviside step function, used to characterize the volume compensation effect that is triggered only when the peak temperature exceeds the phase transition initiation temperature.

[0009] A further technical solution: The total target clamping force prediction module couples the calculated thermal expansion stress component with the phase transformation stress correction factor to obtain the equivalent thermal stress component after phase transformation correction. ;like ,but This is used to quantitatively characterize the increase in additional restraint reaction force caused by the volume expansion due to phase change; simultaneously, the equivalent thermal stress components after phase change correction are predicted through the total target clamping force prediction module. Non-rigid deformation force extracted by the measurement comparison module Combine these methods to solve for the overall target clamping force.

[0010] A further technical solution: The calculation formula for the total target clamping force output by the total target clamping force prediction module is as follows: , in, For the overall target clamping force, For workpiece thickness, This is the thermal expansion stress component. The phase transformation-induced plastic stress constant, This is the phase transformation stress correction factor. , This is a correction factor.

[0011] A further technical solution: The clamping force distribution module determines the weighting coefficient of the clamping point distribution based on the curvature change at each clamping point and the interaction distance between that point and the weld, thereby achieving non-uniform distribution of the clamping force; the weighting coefficient of the clamping point distribution is jointly determined by the local curvature influence factor and the heat source distance attenuation factor, satisfying the following relationship: , in, For the first The weighting coefficients assigned to each clamping point. For the first The absolute value of the principal curvature change at each clamping point (characterizing the degree of local geometric abrupt change). For the first The Euclidean distance from each clamping point to the weld centerline The thermally affected distance decay constant, This represents the total number of clamping points.

[0012] Further technical solution: The collaborative compensation controller corrects the spatial motion posture of the welding execution end in real time, including compensation for the welding torch tilt angle, oscillation amplitude, or welding trajectory; the formula for calculating the output posture correction amount is: , in, This is the attitude correction amount. As a theoretical stance, This is the collaborative compensation coefficient (a compensation coefficient with a unit of length). For the first One clamping point at Load fluctuation value at time, For the first The real-time normal distance of each clamping point from the weld. The elastic modulus of the material. Let be the moment of inertia of the cross section at the corresponding position of the workpiece.

[0013] A further technical solution: The collaborative compensation controller is connected to the welding robot controller through a two-way communication link, and converts the clamping point mechanical change characteristics collected by the load sensor into motion compensation commands for the welding robot in real time.

[0014] This invention provides a welding positioning fixture for sheet metal parts of engineering machinery, which has the following advantages compared with the prior art: This invention accurately extracts the spatial posture deviation and non-rigid deformation force characteristics of the workpiece through a measurement and comparison module, and incorporates a phase transformation stress correction factor calculation unit to compensate for the load requirements caused by thermal expansion and material phase transformation (such as the effect of microstructure volume expansion), thereby calculating the total target clamping force. The clamping force distribution module can dynamically distribute the clamping force non-uniformly to each actuator according to the curvature change of the clamping point and the distance from the weld, effectively constraining the thermal instability of the workpiece. The present invention installs a load sensor on the clamping actuator to monitor load fluctuations in real time and output feedback signals. The collaborative compensation controller can adjust the output force of the clamping mechanism synchronously according to the signal, and simultaneously correct the spatial motion posture of the welding execution end (such as welding torch tilt angle, swing amplitude or welding trajectory), thereby accurately and actively offsetting the thermal deformation displacement of the workpiece and greatly improving the welding accuracy. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the process of the present invention. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0017] The specific implementation of the present invention will be described in detail below with reference to specific embodiments.

[0018] Please see Figure 1 According to one embodiment of the present invention, a welding positioning fixture for sheet metal parts of engineering machinery includes: The measurement and comparison module acquires the measured spatial data of the sheet metal parts and compares it with the theoretical design model to extract the spatial posture deviation of the workpiece and the non-rigid deformation force characteristics that reflect the residual stress state inside the parts. The total target clamping force prediction module calculates the total target clamping force to constrain the thermal instability of the workpiece based on the spatial attitude deviation and non-rigid deformation force characteristics, combined with the phase transformation characteristics of the material. The clamping force distribution module dynamically distributes the total target clamping force to each actuator and determines the initial force component at each clamping point. Multiple clamping actuators are arranged around the workpiece to receive the initial component force output by the clamping force distribution module and apply it to the workpiece; A load sensor is installed on each of the clamping actuators to monitor load fluctuations at each clamping point in real time and output a load feedback signal. The collaborative compensation controller is communicatively connected to the load sensor, the clamping actuator, and the welding robot controller, respectively. It is used to synchronously adjust the output force of the clamping actuator according to the load feedback signal and collaboratively correct the spatial motion posture of the welding execution end to counteract the thermal deformation displacement of the workpiece.

[0019] The following example will provide a more detailed explanation of the above technical solution: Suppose that during the manufacturing process of engineering machinery, a large sheet metal part for an excavator chassis needs to be welded. Due to its complex geometry and manufacturing process, this part may have slight twisting and local stress concentration before welding. These are spatial attitude deviations and non-rigid deformation force characteristics mentioned in the background art. At the same time, during the welding process, high temperatures will cause thermal expansion and phase transformation of the material, leading to thermal instability and deformation of the part.

[0020] First, before the welding operation begins, the excavator chassis sheet metal part is placed on the welding positioning fixture of this embodiment. The measurement and comparison module is activated, acquiring the measured three-dimensional spatial point cloud data of the sheet metal part through a non-contact laser scanner. Subsequently, the module accurately compares these measured data with the pre-imported theoretical CAD design model of the excavator chassis part. Through a complex geometric matching algorithm, the measurement and comparison module can accurately identify the overall rigid displacement of the part (e.g., slight tilting or translation of the part on the fixture) and the non-rigid deformation of local areas (e.g., slight warping or concavity of the edges), and quantify them as spatial attitude deviations and non-rigid deformation force characteristics.

[0021] Next, the total target clamping force prediction module receives the deviation data output by the measurement comparison module. This module combines the phase transformation characteristics (such as the volume expansion effect during the transformation from austenite to martensite) of the chassis part material (e.g., high-strength steel) in the preset material database, and calculates the total target clamping force required to effectively suppress the thermal instability of the part throughout the welding process using a built-in prediction model. This calculation takes into account the initial deformation energy and the dynamic deformation that may be caused by the welding heat input.

[0022] Subsequently, the clamping force distribution module dynamically distributes the total target clamping force to multiple clamping actuators arranged around the part based on the calculation results of the total target clamping force prediction module and in combination with the geometric characteristics of the chassis part (e.g., some areas have large curvature changes or are close to the main weld). For example, for areas with large local deformation or close to the weld, a higher initial clamping force may be allocated to provide stronger constraint.

[0023] During the welding process, multiple clamping actuators (e.g., hydraulically driven clamps) apply precise clamping forces to the chassis parts according to the initial force determined by the clamping force distribution module. Simultaneously, load sensors mounted on each clamping actuator continuously monitor the load fluctuations it experiences in real time. When the welding heat source passes, the parts locally expand due to heat, potentially causing a momentary increase in the load at adjacent clamping points; conversely, during cooling and contraction, the load may decrease. These load fluctuations are precisely captured by the load sensors and converted into load feedback signals.

[0024] Ultimately, the collaborative compensation controller receives real-time load feedback signals from all load sensors. This controller communicates with each clamping actuator and the welding robot controller via a high-speed data link. Based on the load feedback signals, the collaborative compensation controller can determine the deformation trend and degree of the part in real time. For example, if the clamping force in a certain area continues to increase, it indicates that significant thermal expansion is occurring in that area. In this case, the collaborative compensation controller will immediately send instructions to the corresponding clamping actuator to synchronously adjust its output force to maintain the preset clamping force or provide appropriate flexible constraint. Furthermore, the collaborative compensation controller also predicts the real-time thermal deformation displacement of the workpiece in front of the welding execution end (i.e., the welding torch) based on the overall load fluctuation pattern. This controller converts this prediction information into motion compensation commands and sends them to the welding robot controller via the communication link, thereby collaboratively correcting the spatial motion posture of the welding execution end, such as fine-tuning the welding torch's tilt angle, oscillation amplitude, or welding trajectory. Through this dynamic and collaborative compensation mechanism, the thermal deformation displacement generated by the workpiece during welding can be effectively offset, ensuring the final welding quality and dimensional accuracy.

[0025] Compared to the traditional welding fixtures mentioned in the background art, the measurement and comparison module of this embodiment can accurately extract the spatial posture deviation of the workpiece and the non-rigid deformation force characteristics that reflect the residual stress state inside the part by acquiring the measured spatial data of the sheet metal part and comparing it with the theoretical design model. This data-driven initial state assessment overcomes the limitations of existing technologies that rely solely on experience or simple positioning, and provides a solid foundation for subsequent precise control.

[0026] Preferably, the measurement comparison module utilizes the deviation field between spatial point cloud data and theoretical numerical model, and decouples the global rigid body displacement deviation and local non-rigid deformation force through a singular value decomposition algorithm. The solution process satisfies the following relationship: Solving for rigid body transformation parameters: The global rotation matrix and translation vector are solved by minimizing the Euclidean distance between point sets. , in, This is a global rotation matrix. It is a translation vector. The measured feature point spatial vector, For the spatial vector of the theoretical feature points; Calculation of non-rigid deformation force characteristics: After eliminating rigid body displacements using the solved global rotation matrix and translation vector, the equivalent deformation force is calculated. , in, For deformation and other effects, The material shear modulus This is a global rotation matrix. It is a translation vector. The measured feature point spatial vector, The spatial vector of the theoretical feature point.

[0027] Specifically, the deviation field between the spatial point cloud data and the theoretical model refers to the spatial difference distribution obtained by comparing the point cloud data of the actual geometric shape of the workpiece acquired by a 3D scanning device (such as a laser scanner, structured light scanner, or industrial CT) with a pre-established computer-aided design (CAD) model of the ideal geometric shape of the workpiece. This deviation field intuitively reflects the geometric inconsistency between the actual workpiece and the theoretical model. The singular value decomposition algorithm is a powerful linear algebra tool that can decompose a matrix into the product of three matrices. It has wide applications in data analysis and geometric transformation. Here, it is used to accurately separate the overall rigid body motion (such as translation and rotation) of the workpiece and its local elastic or plastic deformation from the complex deviation field. The global rigid body displacement deviation refers to the position and orientation change of the workpiece as a whole in space, without involving changes in its own shape. The local non-rigid deformation force refers to the energy contained in the shape change of the workpiece due to internal stress, external load, or manufacturing defects. It directly reflects the degree and trend of the workpiece's deformation.

[0028] The solution in this application achieves its function in the following way: First, the measurement and comparison module acquires the measured spatial data of the sheet metal part, usually presented in the form of a high-density spatial point cloud. Simultaneously, this module loads the theoretical design model of the workpiece, which is typically a CAD model. Then, the module compares the measured spatial point cloud data with the theoretical model to generate an initial deviation field. To accurately distinguish between the overall rigid displacement and local deformation of the workpiece, the measurement and comparison module employs a singular value decomposition algorithm. This algorithm first solves for the optimal global rotation matrix and translation vector by minimizing the Euclidean distance between the measured feature point spatial vector and the theoretical feature point spatial vector after rotation and translation transformation. This process effectively separates the overall rigid displacement of the workpiece from the total deviation. After determining and applying the global rotation matrix and translation vector to eliminate rigid displacement, the measurement and comparison module further calculates the deformation equivalent force as a key feature reflecting the residual stress state inside the part. In this way, the measurement and comparison module can accurately decouple the global rigid displacement deviation and local non-rigid deformation force, and transmit these precise feature data to the overall target clamping force prediction module. This precise decoupling ensures the accuracy of subsequent clamping force prediction, avoiding misjudgments and improper clamping caused by confusion between rigid body displacement and non-rigid deformation, thus providing a solid foundation for achieving precise welding positioning and effectively suppressing thermal deformation.

[0029] The following is a concrete example. Before welding a sheet metal part of a large engineering machine, a high-precision 3D laser scanner is used to scan the area to be welded, acquiring the spatial coordinates of millions of points on its surface to form spatial point cloud data. Simultaneously, the theoretical CAD model of the sheet metal part is obtained from the design department. After receiving the point cloud data and the CAD model, the measurement and comparison module first performs a point cloud registration operation. This operation uses a singular value decomposition algorithm, employing iterative nearest point (ICP) or direct SVD methods to calculate the optimal rigid body rotation matrix and translation vector of the point cloud relative to the CAD model. For example, if the point cloud is translated 5mm along the X-axis and rotated 2 degrees around the Z-axis relative to the CAD model, the SVD algorithm can accurately identify these rigid body transformation parameters. After eliminating these rigid body displacements, the measurement and comparison module calculates the residual distance between each point in the point cloud and its corresponding point in the CAD model. These residual distances no longer contain rigid body displacement components but are purely caused by local deformation of the workpiece. Subsequently, based on the preset material shear modulus, these residual distances are converted into deformation energy density using the non-rigid deformation force characteristic calculation formula, thereby quantifying the degree of non-rigid deformation of the workpiece.

[0030] Through the above technical solution, the measurement and comparison module can accurately distinguish between the overall rigid displacement and local non-rigid deformation of the workpiece. This precise decoupling avoids misjudging the overall positional deviation of the workpiece as deformation requiring clamping force compensation, thereby preventing unnecessary or incorrect clamping force application. Therefore, the overall target clamping force prediction module can calculate the required clamping force based on more accurate non-rigid deformation force characteristics, ensuring that the clamping force only acts on the area that truly needs deformation suppression, improving the accuracy of the clamping strategy. This not only helps optimize the distribution of clamping force and reduce thermal deformation of the workpiece during welding, but also effectively reduces welding residual stress, ultimately improving welding quality and product dimensional accuracy.

[0031] Preferably, in the total target clamping force prediction module, the phase transformation characteristics include the microstructure volume expansion effect of the material during the welding cooling process. The module has a built-in phase transformation stress correction factor calculation unit, which is used to compensate for the load demand caused by thermal expansion and initial deformation energy. The compensation control calculation process is as follows. Define the thermal expansion stress components as: , in, This is the thermal expansion stress component. The elastic modulus of the material. This is the coefficient of linear expansion of the material. This is the peak welding temperature. The initial ambient temperature; The phase transformation stress correction factor output by the phase transformation stress correction factor calculation unit is set as follows: , in, This is the phase transformation stress correction factor. This represents the rate of change per unit volume during the phase transition process. The stress transfer coefficient of the tissue. Peak temperature The phase transition initiation temperature, , is the Heaviside step function (used to characterize the volume compensation effect that is triggered only when the peak temperature exceeds the phase transition initiation temperature). The compensation logic specifically involves the total target clamping force prediction module multiplying and coupling the calculated thermal expansion stress component with the phase transformation stress correction factor to obtain the equivalent thermal stress component after phase transformation correction. ;like ,but This is used to quantitatively characterize the increase in additional restraint reaction force caused by the volume expansion due to phase change; simultaneously, the equivalent thermal stress components after phase change correction are predicted through the total target clamping force prediction module. Non-rigid deformation force extracted by the measurement comparison module Combining these factors, the total target clamping force is calculated. The formula for calculating the total target clamping force output by the total target clamping force prediction module is as follows: , in, For the overall target clamping force, For workpiece thickness, This is the thermal expansion stress component. The phase transformation-induced plastic stress constant, This is the phase transformation stress correction factor. , This is a correction factor.

[0032] The phase transformation characteristic refers to the physical and mechanical behavior exhibited by a material during the heating and cooling process of welding, resulting in a transformation of its internal crystal structure. This characteristic can include, but is not limited to, changes in crystal structure, density or volume, and the resulting internal stress. For example, for steel, austenitization occurs at the high temperature of welding, and during cooling, martensitic, bainitic, or pearlitic phase transformations may occur. These phase transformations are usually accompanied by volume expansion or contraction. The microstructure volume expansion effect is a specific manifestation of the phase transformation characteristic, specifically referring to the phenomenon that the macroscopic volume of a material expands due to crystal structure rearrangement during the cooling process from a high-temperature phase to a low-temperature phase. This effect is particularly important during the welding cooling process because it directly affects the stress distribution and deformation trend of the workpiece. For example, the transformation from austenite to martensite is usually accompanied by significant volume expansion. The phase transformation stress correction factor calculation unit is a functional module that compensates for the load requirements caused by welding thermal expansion and the initial deformation energy of the workpiece. This unit can be an independent software module embedded in the total target clamping force prediction module, or a dedicated hardware circuit used to calculate the impact of phase transformation on clamping force requirements in real time or near real time. Its implementation can be achieved through a preset lookup table, a real-time calculation program based on a physical model, or a combination of machine learning algorithms. The compensation control calculation process is a series of mathematical operations within the total target clamping force prediction module used to accurately calculate the total target clamping force. This process first quantifies the stress generated by the material due to temperature rise by defining thermal expansion stress components. Then, a phase transformation stress correction factor is introduced to characterize the additional effect of phase transformation volume expansion on the restraint reaction force. Finally, these corrected stress components are combined with non-rigid deformation forces to more comprehensively predict the required total target clamping force.

[0033] The solution proposed in this application improves the accuracy of constraining the thermal instability of the workpiece by deeply considering the phase transformation characteristics of the material, especially the microstructure volume expansion effect, in the overall target clamping force prediction module. Specifically, the measurement and comparison module first acquires the spatial orientation deviation and non-rigid deformation force characteristics of the workpiece, providing basic data for subsequent clamping force calculation. Based on this, the overall target clamping force prediction module no longer relies solely on macroscopic deformation energy, but further incorporates a phase transformation stress correction factor calculation unit. This unit can calculate the phase transformation stress correction factor based on the material's elastic modulus. Coefficient of linear expansion Peak welding temperature and initial ambient temperature Accurately calculate the thermal expansion stress components More importantly, this unit can also determine the rate of change per unit volume during the phase transition process. Tissue stress transfer coefficient Phase transition initiation temperature Parameters, combined with the Heaviside step function Dynamically generate phase transformation stress correction factor When the peak welding temperature Exceeding the phase transition initiation temperature At that time, the correction factor The value will be greater than 1, quantitatively reflecting the increase in additional restraint reaction force caused by the volume expansion due to phase change. Subsequently, the total target clamping force prediction module will calculate the thermal expansion stress components. With phase transformation stress correction factor By performing product coupling, the equivalent thermal stress components after phase transition correction are obtained. Ultimately, the module modifies this phase transition-corrected equivalent thermal stress component. Non-rigid deformation force extracted by the measurement comparison module Combined, taking into account the workpiece thickness Phase transformation induced plastic stress constant and correction factor , A more accurate total target clamping force can be calculated using a specific formula. This mechanism ensures that even if the material undergoes complex phase transformations during the welding process, the required clamping force can be accurately predicted, thus providing a more reliable input to the clamping force distribution module, and ultimately achieving effective compensation of the workpiece's thermal deformation displacement through the clamping actuator and the collaborative compensation controller.

[0034] As one specific implementation, the total target clamping force prediction module can be implemented as an embedded software program running on an industrial controller or high-performance computing unit. This program includes a subroutine for calculating the phase transformation stress correction factor. Before welding begins, the elastic modulus of the sheet metal to be welded can be obtained from a material database. Coefficient of linear expansion Rate of change per unit volume during phase transition Tissue stress transfer coefficient Phase transition initiation temperature and phase transformation induced plastic stress constant Parameters such as initial ambient temperature The peak welding temperature can be obtained through environmental sensors. It can be monitored in real time via a thermocouple array, or predicted through finite element thermo-mechanical coupling simulation. Once the welding process begins, the phase transformation stress correction factor calculation subroutine will calculate the phase transformation stress based on real-time or predicted values. , combined Determine whether the volume compensation effect is triggered and calculate the phase transformation stress correction factor. Then, the main program will... , , , Calculate thermal expansion stress components and with Multiplying yields the equivalent thermal stress components after phase transition correction. Meanwhile, the measurement and comparison module will continuously provide non-rigid deformation force. Finally, the total target clamping force prediction module substitutes these parameters into the total target clamping force. The calculation formula yields the total target clamping force required at the current moment. For example, for Q345 steel, its martensitic transformation initiation temperature... It's probably around 400℃, when the peak welding temperature... At temperatures much higher than this, the phase transformation stress correction factor... It will be significantly greater than 1, thus affecting the total target clamping force. Additional constraint reaction force increments are introduced into the calculations to address the volume expansion caused by the martensitic phase transformation.

[0035] Through the above technical solution, this application fully considers the volumetric expansion effect of the material during welding cooling when predicting the total target clamping force. By introducing a phase transformation stress correction factor calculation unit and combining it with the thermal expansion stress components for product coupling, the incremental additional restraint reaction force caused by the volumetric expansion due to phase transformation can be quantified more accurately. This allows the total target clamping force prediction module to output a clamping force value that more closely matches the actual stress state of the workpiece, thereby significantly improving the prediction accuracy and control capability for workpiece thermal instability. Compared with schemes that only consider rigid body displacement and non-rigid deformation forces, this application can more effectively counteract the complex deformation of the workpiece caused by phase transformation during welding, reduce welding residual stress and deformation, and ultimately improve the welding quality and dimensional accuracy of sheet metal parts for engineering machinery.

[0036] Preferably, the clamping force distribution module determines the weighting coefficient of the clamping point distribution based on the curvature change at each clamping point and the interaction distance between that point and the weld, thereby achieving non-uniform distribution of the clamping force. The weighting coefficient of the clamping point distribution is jointly determined by the local curvature influence factor and the heat source distance attenuation factor, satisfying the following relationship: , in, For the first The weighting coefficients assigned to each clamping point. For the first The absolute value of the principal curvature change at each clamping point (characterizing the degree of local geometric abrupt change). For the first The Euclidean distance from each clamping point to the weld centerline The thermally affected distance decay constant, This represents the total number of clamping points.

[0037] The clamping force distribution module is a control unit responsible for rationally distributing the total target clamping force calculated by the system to each clamping actuator. This module can be an independent microcontroller, an embedded system, or a software function module within the main controller. Its main function is to receive the total target clamping force and, based on a preset distribution strategy or real-time calculated weighting coefficients, output the specific clamping force commands required for each clamping point. The curvature change at the clamping point refers to the degree of bending of the workpiece surface geometry near each clamping point. Areas with large curvature changes usually indicate relatively weak structural stiffness or complex geometry, making them more prone to deformation. This curvature change can be obtained through pre-analysis of the workpiece's CAD model, for example, by calculating the absolute value of Gaussian curvature or principal curvature; or, in actual production, by acquiring the actual geometric data of the workpiece using a 3D scanning device and performing curvature analysis. The interaction distance between the clamping point and the weld refers to the Euclidean distance from each clamping point to the welding heat source (i.e., the weld centerline). The closer the area is to the weld, the greater the influence of the welding heat input, and the higher the risk of thermal deformation. This distance can be determined using the workpiece's CAD model or actual welding path planning data. The weighting coefficients for clamping point allocation are values ​​used to quantify the proportion of total clamping force that each clamping point should bear. The determination of these coefficients directly affects the non-uniform distribution effect of clamping force. Non-uniform distribution of clamping force refers to applying different clamping forces to each clamping point based on the deformation sensitivity, geometric characteristics, and degree of heat influence of different areas of the workpiece. This allocation method aims to concentrate more clamping force on areas that are more prone to deformation or are more affected by heat, thereby improving the overall deformation control effect. The weighting coefficients for clamping point allocation are jointly determined by the local curvature influence factor and the heat source distance attenuation factor. The local curvature influence factor reflects the geometric complexity or deformation sensitivity of the area where the clamping point is located; for example, it can be related to the absolute value of the principal curvature change at the clamping point location. The heat source distance attenuation factor is directly proportional to the welding heat source and reflects the degree to which the clamping point is affected by the welding heat source. Generally, the closer to the weld, the larger the factor. For example, it can be related to an exponential attenuation function, which includes the Euclidean distance from the clamping point to the weld centerline. and thermal effect distance decay constant .

[0038] This application's solution overcomes the limitations of traditional uniform clamping force distribution in welding complex sheet metal parts by introducing an intelligent clamping force distribution strategy. Specifically, the clamping force distribution module no longer simply distributes the total target clamping force evenly. Instead, it first acquires the geometric characteristics of each clamping point location, i.e., curvature changes, and its relative position to the welding heat source, i.e., the interaction distance with the weld. This information is crucial for assessing the deformation sensitivity and thermal influence of each clamping point area. Based on this information, the clamping force distribution module calculates a unique weighting coefficient for each clamping point. The calculation of this weighting coefficient takes into account the influence of local curvature factors. and heat source distance attenuation factor Among them, the local curvature influence factor The curvature change directly reflects the degree of geometric abrupt change in the clamping point area. The greater the curvature change, the more prone the area is to deformation, thus requiring a larger clamping force to restrain it. The heat source distance attenuation factor reflects the influence of the welding heat source on the clamping point. The closer the clamping point is to the weld, the greater the impact of thermal deformation, and the greater the clamping force required to counteract it. By multiplying and coupling these two factors and normalizing them, the sum of the weight coefficients of all clamping points is ensured to be 1, thereby enabling the total target clamping force to be precisely distributed. This non-uniform distribution mechanism allows the clamping force to be applied "on demand," that is, a larger clamping force is applied to areas with complex geometry, easy deformation, or those near the weld that are greatly affected by heat, while a smaller clamping force is applied to relatively flat areas far from the weld. This not only more effectively suppresses the thermal deformation of the workpiece during the welding process, but also avoids applying excessive force in areas where large clamping forces are not needed, thereby reducing unnecessary stress concentration and potential workpiece damage. Through this refined clamping force distribution, the solution of this application can significantly improve the control accuracy and effect of sheet metal welding deformation, ensuring welding quality and dimensional accuracy.

[0039] The following is a concrete example to illustrate this. The clamping force distribution module can be integrated into an industrial PC or PLC. It uses pre-loaded workpiece CAD model data and welding path planning data to obtain the curvature changes at clamping point locations and the interaction distance with the weld seam. For example, when welding a sheet metal part with complex curved edges, the clamping force distribution module first extracts the principal surface curvature information at all preset clamping points from the CAD model and calculates its absolute value as a local curvature influence factor. Simultaneously, based on the welding path, the shortest distance from each clamping point to the weld centerline is calculated. Thermally affected distance decay constant The clamping force can be set empirically based on material type and welding process parameters, or determined through simulation optimization. Subsequently, the clamping force distribution module calculates the weighting coefficient for each clamping point using a formula. For example, the weighting coefficient for clamping points near the weld with significant curvature changes will be significantly higher than that for clamping points far from the weld with gentler curvature. Assume the total target clamping force is... Then the first The initial component force that should be applied at each clamping point is These calculated initial force commands are then sent to the corresponding clamping actuators, such as pneumatic or electric clamps, to achieve precise non-uniform clamping of the workpiece.

[0040] Through the above technical solution, this application overcomes the shortcomings of traditional clamping force distribution methods in dealing with welding deformation of complex sheet metal parts. By comprehensively considering the local geometric features (curvature changes) and thermal influence characteristics (interaction distance with the weld) of the clamping point, non-uniform and intelligent distribution of clamping force is achieved. This distribution method allows the clamping force to act more precisely on the key deformation areas of the workpiece, effectively suppressing local thermal deformation and stress concentration caused by uneven heat input and geometric complexity during welding. This not only improves the accuracy and stability of welding positioning and significantly reduces residual deformation after welding, but also optimizes the efficiency of clamping force utilization, avoiding unnecessary excessive clamping of the workpiece, thereby improving the welding quality and production efficiency of sheet metal parts for engineering machinery.

[0041] Preferably, the collaborative compensation controller's spatial motion posture correction at the welding execution end includes real-time compensation for the welding torch tilt angle, oscillation amplitude, or welding trajectory, and the formula for calculating the output posture correction amount is as follows: ,

[0042] in, This is the attitude correction amount. As a theoretical stance, This is the collaborative compensation coefficient (a compensation coefficient with a unit of length). For the first One clamping point at Load fluctuation value at time, For the first The real-time normal distance of each clamping point from the weld. The elastic modulus of the material. Let be the moment of inertia of the cross section at the corresponding position of the workpiece.

[0043] Among these, the spatial motion posture correction at the welding end effector refers to adjusting the position and orientation of the welding torch mounted on the welding robot's end effector in three-dimensional space. This correction can be manifested in several ways. For example, real-time compensation for the welding torch tilt angle involves dynamically adjusting the torch's tilt angle relative to the weld seam based on the thermal deformation of the workpiece during welding to ensure the torch maintains the optimal welding angle with the workpiece surface. This can be achieved through fine-tuning of the welding robot joints or a dedicated tilt adjustment mechanism integrated into the end effector. Another example is real-time compensation for the oscillation amplitude, where the width or range of the torch's oscillation is dynamically adjusted based on the workpiece's deformation during oscillating welding to ensure weld uniformity and consistent penetration depth. This can be achieved through robot programming or a dedicated oscillation mechanism. Furthermore, real-time compensation for the welding trajectory involves dynamically correcting the actual path of the welding torch based on the actual deformation of the workpiece, deviating it from the preset theoretical trajectory to precisely adapt to the deformed workpiece surface. This is typically achieved through real-time updates of the welding robot's path planning algorithm. The purpose of these correction methods is to ensure that the welding torch is always in the optimal welding position and posture throughout the welding process to accommodate the geometric changes of the workpiece caused by thermal deformation, thereby ensuring welding quality.

[0044] The formula for calculating attitude correction provides a method for quantifying attitude correction. This method combines the feedback signal from the load sensor with the physical properties of the workpiece (such as the elastic modulus). Moment of inertia of cross section And the distance between the clamping point and the weld. Connect them. Attitude correction amount. This is a crucial output that directly guides the welding robot on how to adjust its end effector posture. The implementation of this formula depends on several factors: First, load sensors monitor the mechanical changes at each clamping point in real time, and these load fluctuation values... It directly reflects the deformation trend and degree of the workpiece under welding heat input; secondly, the formula incorporates the real-time normal distance between the clamping point and the weld. Material elastic modulus Moment of inertia of the cross section at the corresponding position of the workpiece These parameters reflect the workpiece's resistance to deformation and the geometric influence of deformation; in addition, the collaborative compensation coefficient... It is an adjustable parameter used to balance the influence of load fluctuations on the attitude correction amount, and can be calibrated according to the actual welding process and material properties.

[0045] The solution in this application receives load feedback signals from load sensors through a collaborative compensation controller, and uses these signals as inputs, combined with the workpiece's material elastic modulus. Moment of inertia of the cross section at the corresponding position of the workpiece and the real-time normal distance between the clamping point and the weld. The attitude correction amount at the welding execution end is accurately calculated using a preset calculation formula. This attitude correction amount The data is then sent to the welding robot controller by the collaborative compensation controller to adjust the spatial motion posture of the welding end effector in real time, including the welding torch tilt angle, oscillation amplitude, or welding trajectory. This correction mechanism, combined with the synchronous adjustment of the output force of the clamping actuator, forms a comprehensive thermal deformation compensation strategy. By precisely quantifying and correcting the welding torch posture in real time, the system can actively adapt to the complex dynamic deformation of the workpiece during welding, ensuring that the welding torch always maintains the optimal relative position and angle with the deformed workpiece surface, thereby effectively offsetting the thermal deformation displacement of the workpiece and guaranteeing welding quality.

[0046] The following is a concrete example: when welding a large sheet metal part for engineering machinery, multiple clamping actuators are arranged around the workpiece and equipped with load sensors. When the welding robot begins welding, the heat input causes localized expansion and contraction of the workpiece, resulting in deformation. This causes load fluctuations at the clamping points. The load sensors monitor these load fluctuations in real time. This information is then fed back to the collaborative compensation controller. The collaborative compensation controller determines the elastic modulus of the workpiece material based on a pre-set value. Moment of inertia of cross section And combined with the real-time acquired normal distance from each clamping point to the weld. Using the formula for calculating attitude correction, the attitude correction required at the current welding execution end is calculated. For example, if calculations indicate that the workpiece warps upwards in a certain area due to thermal deformation, causing a change in the local tilt angle of the weld, the collaborative compensation controller will immediately send a command to the welding robot controller to adjust the tilt angle of the welding torch, ensuring it remains perpendicular to the deformed workpiece surface or at the preset optimal welding angle. If the workpiece undergoes lateral contraction or expansion during welding, causing a deviation in the weld trajectory, the collaborative compensation controller will correct the welding trajectory, ensuring the welding torch moves precisely along the actual weld path. Collaborative compensation coefficient. The compensation effect can be optimized by calibration through welding experiments or simulation analysis of specific sheet metal parts or by assigning values ​​based on expert experience.

[0047] Through the aforementioned technical solution, the collaborative compensation controller can not only dynamically adjust the clamping force to suppress workpiece deformation, but also, based on real-time load feedback and workpiece physical characteristics, accurately calculate and correct in real-time the welding torch tilt angle, oscillation amplitude, or welding trajectory at the welding execution end. This enables the welding process to proactively adapt to the complex dynamic deformation of the workpiece caused by heat input, ensuring that the welding torch is always in the optimal welding posture and position, thereby significantly improving welding accuracy and quality, effectively avoiding weld defects caused by thermal deformation, and enhancing the robustness and automation level of the entire welding process.

[0048] Preferably, the collaborative compensation controller is connected to the welding robot controller via a two-way communication link, and converts the clamping point mechanical change characteristics collected by the load sensor into motion compensation commands for the welding robot in real time.

[0049] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus.

[0050] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A welding positioning fixture for sheet metal parts of engineering machinery, characterized in that, include: The measurement and comparison module acquires the measured spatial data of the sheet metal parts and compares it with the theoretical design model to extract the spatial posture deviation of the workpiece and the non-rigid deformation force characteristics that reflect the residual stress state inside the parts. The total target clamping force prediction module calculates the total target clamping force to constrain the workpiece's thermal instability based on the spatial attitude deviation and non-rigid deformation force characteristics, combined with the phase transformation characteristics of the material. The clamping force distribution module dynamically distributes the total target clamping force to each actuator and determines the initial force component at each clamping point. Multiple clamping actuators are arranged around the workpiece to receive the initial component force output by the clamping force distribution module and apply it to the workpiece; A load sensor is installed on each of the clamping actuators to monitor load fluctuations at each clamping point in real time and output a load feedback signal. The collaborative compensation controller is communicatively connected to the load sensor, the clamping actuator, and the welding robot controller, respectively. It is used to synchronously adjust the output force of the clamping actuator according to the load feedback signal and collaboratively correct the spatial motion posture of the welding execution end to counteract the thermal deformation displacement of the workpiece.

2. The welding positioning fixture for sheet metal parts of engineering machinery according to claim 1, characterized in that, The measurement and comparison module utilizes the deviation field between spatial point cloud data and theoretical numerical models, and decouples the global rigid body displacement deviation and local non-rigid deformation force through a singular value decomposition algorithm. Its calculation process satisfies the following relationship: Solving for rigid body transformation parameters: The global rotation matrix and translation vector are solved by minimizing the Euclidean distance between point sets. ， in, This is a global rotation matrix. It is a translation vector. The measured feature point spatial vector, For the spatial vector of the theoretical feature points; Calculation of non-rigid deformation force characteristics: After eliminating rigid body displacements using the solved global rotation matrix and translation vector, the equivalent deformation force is calculated. ， in, For deformation and other effects, The material shear modulus This is a global rotation matrix. It is a translation vector. The measured feature point spatial vector, The spatial vector of the theoretical feature point.

3. The welding positioning fixture for sheet metal parts of engineering machinery according to claim 1, characterized in that, In the total target clamping force prediction module, the phase transformation characteristics include the microstructure volume expansion effect of the material during the welding cooling process. This module has a built-in phase transformation stress correction factor calculation unit, which is used to compensate for the load demand caused by thermal expansion and initial deformation energy. The compensation control calculation process is as follows: Define the thermal expansion stress components as: ， in, This is the thermal expansion stress component. The elastic modulus of the material. is the coefficient of linear expansion of the material. This is the peak welding temperature. The initial ambient temperature; The phase transformation stress correction factor output by the phase transformation stress correction factor calculation unit is set as follows: ， in, This is the phase transformation stress correction factor. This represents the rate of change per unit volume during the phase transition process. The stress transfer coefficient of the tissue. Peak temperature The phase transition initiation temperature, is the Heaviside step function, used to characterize the volume compensation effect that is triggered only when the peak temperature exceeds the phase transition initiation temperature; The total target clamping force prediction module couples the calculated thermal expansion stress component with the phase transformation stress correction factor to obtain the equivalent thermal stress component after phase transformation correction. ; The equivalent thermal stress component after phase transformation correction is obtained through the total target clamping force prediction module. Non-rigid deformation force extracted by the measurement comparison module Combine these methods to solve for the overall target clamping force.

4. The welding positioning fixture for sheet metal parts of engineering machinery according to claim 3, characterized in that, The formula for calculating the total target clamping force output by the total target clamping force prediction module is as follows: ， in, For the overall target clamping force, For workpiece thickness, This is the thermal expansion stress component. The phase transformation-induced plastic stress constant, This is the phase transformation stress correction factor. , This is a correction factor.

5. The welding positioning fixture for sheet metal parts of engineering machinery according to claim 1 or 4, characterized in that, The clamping force distribution module determines the weighting coefficient for clamping point allocation based on the curvature change at each clamping point and the interaction distance between that point and the weld, thereby achieving non-uniform distribution of clamping force. The weighting coefficient for clamping point allocation is jointly determined by the local curvature influence factor and the heat source distance attenuation factor, satisfying the following relationship: ， in, For the first The weighting coefficients assigned to each clamping point, For the first The absolute value of the principal curvature change at each clamping point location For the first The Euclidean distance from each clamping point to the weld centerline The thermally affected distance decay constant, This represents the total number of clamping points.

6. The welding positioning fixture for sheet metal parts of engineering machinery according to claim 1, characterized in that, The collaborative compensation controller corrects the spatial motion posture of the welding execution end in real time, including compensation for the welding torch tilt angle, oscillation amplitude, or welding trajectory; the formula for calculating the output posture correction amount is as follows: ， in, This is the attitude correction amount. As a theoretical stance, It is a coefficient for collaborative compensation and has the dimension of length. For the first One clamping point at Load fluctuation value at time, For the first The real-time normal distance of each clamping point from the weld. The elastic modulus of the material. Let be the moment of inertia of the cross section at the corresponding position of the workpiece.

7. The welding positioning fixture for sheet metal parts of engineering machinery according to any one of claims 1-6, characterized in that, The collaborative compensation controller is connected to the welding robot controller via a two-way communication link, and converts the mechanical change characteristics of the clamping point collected by the load sensor into motion compensation commands for the welding robot in real time.

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